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Customer Segmentation (RFM Analysis)
Python notebook using data from UCI Online Retail II Data Set · 182 views · 7mo ago·exploratory data analysis, categorical data
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14
Tensor Girl
Merve Torkan
Simge Erek
Mehmet A.
Ahmet Can Karaoğlan
MEHMET KELEŞ
ILKER YILDIZ
Ayyuce Kaytazci
Arif Eker
Işıl Güler
Fikret Aysel
Cemal Cem Tastan
babyoda
Eray Can Eroğul
Input
43.51 MB
folder

Data Sources

      arrow_drop_down

      UCI Online Retail II Data Set

      UCI Online Retail II Data Set
          arrow_drop_down
          calendar_view_week

          online_retail_II.xlsx

          online_retail_II.xlsx (43.51 MB)
              calendar_view_week

              Year 2009-2010

              Year 2009-2010 (525k rows)
              calendar_view_week

              Year 2010-2011

              Year 2010-2011 (542k rows)
online_retail_II.xlsx(43.51 MB)
get_app
Download
TableTotal RowsTotal Columns
Year 2009-20105254618
Year 2010-20115419108
Output
5.15 KB
      calendar_view_week

      champions.csv

      champions.csv (3.57 KB)
      calendar_view_week

      need_attentions.csv

      need_attentions.csv (1.25 KB)
      calendar_view_week

      new_customers.csv

      new_customers.csv (344 B)
champions.csv(3.57 KB)
get_app
Download
ChampionsID
12347
12362
12364
12381
12417
12423
12429
12433
12437
12451
12471
12490
12518
12524
12526
12528
12553
12560
12562
12569
12572
12583
12584
12598
12615
12621
12627
12630
12662
12668
12670
12682
12683
12684
12700
12704
12714
12716
12720
12723
12727
12747
12748
12749
12762
12766
12782
12783
12784
Execution Info
Succeeded
True
Exit Code
0
Used All Space
False
Run Time
213.9 seconds
Timeout Exceeded
False
Output Size
5.15 KB
Accelerator
None
TimeLine #Log Message
197.7s1/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning:
197.7s2A value is trying to be set on a copy of a slice from a DataFrame
197.7s3
197.7s4See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
197.7s5 """Entry point for launching an IPython kernel.
199.4s6Data Frame Raws Lenght : 397925
199.4s7Data Frame Columns Lenght : 9
199.4s8
199.4s9Data Frame Columns Names : ['Invoice', 'StockCode', 'Description', 'Quantity', 'InvoiceDate', 'Price', 'Customer ID', 'Country', 'TotalPrice']
199.4s10
...
201.6s60 """Entry point for launching an IPython kernel.
203.7s61(4339,) (4339, 1) (4339, 1)
209.1s62Total Amount : 8911425.904
209.1s63Champions' expenditures: 4218731.989999999
209.1s64Need attention expenditures : 177573.90999999997
209.1s65New customer expenditures: 205817.31999999998
210.7s66[NbConvertApp] Converting notebook __notebook__.ipynb to notebook
211.6s67[NbConvertApp] Writing 134981 bytes to __notebook__.ipynb
212.3s68[NbConvertApp] Converting notebook __notebook__.ipynb to html
213.8s69[NbConvertApp] Writing 382280 bytes to __results__.html
213.8s70
213.8s71...
Complete. Exited with code 0.

Comments (15)

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babyodaPosted on Version 3 of 3 • 7 months agoOptions

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7

Great study, i will take this as a guidebook in RFM 👍, I have uploaded a RFM example data, I would be honored to see you work on it

Burak BüyükyağmurTopic AuthorPosted on Version 3 of 3 • 7 months agoOptions

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I will check your datasets, thank you for your support.

Arif EkerPosted on Version 3 of 3 • 7 months agoOptions

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Müşterileriniz hangi durumda? Cevabı burada 👈

Burak BüyükyağmurTopic AuthorPosted on Version 3 of 3 • 7 months agoOptions

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All is yours 👍

MEHMET KELEŞPosted on Version 3 of 3 • 7 months agoOptions

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Great work 👍

Cemal Cem TastanPosted on Version 3 of 3 • 7 months agoOptions

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5

here is one more awesome notebook from Burak.
a well explained and very well analysed segmentation problem.
you know how this is done, buddy!

Burak BüyükyağmurTopic AuthorPosted on Version 3 of 3 • 7 months agoOptions

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That's my lovely teammate. I can feel your support all the time ! Thank you. 😊

Ayyuce KaytazciPosted on Version 3 of 3 • 7 months agoOptions

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Congrats, great kernel. Thank you for sharing. 🙏

Burak BüyükyağmurTopic AuthorPosted on Version 3 of 3 • 7 months agoOptions

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Thanks. 🙏

Işıl GülerPosted on Version 3 of 3 • 7 months agoOptions

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6

Well explained study!

Burak BüyükyağmurTopic AuthorPosted on Version 3 of 3 • 7 months agoOptions

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I am glad to like it. 😊

Mehmet A.Posted on Version 3 of 3 • 7 months agoOptions

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great job @burakbuyukyagmur i wonder why you used 3 segmentation ? I am curious if we can do 4 segmentation what can be change ? :)

Burak BüyükyağmurTopic AuthorPosted on Version 3 of 3 • 7 months agoOptions

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I think, We can add one more capital letter to RFM - ? 🤓
What do you say ? 🙏🙏

Merve TorkanPosted on Version 3 of 3 • 7 months agoOptions

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You are very good teammate 💚this is wonderful kernel. Moreover, clean and good explanation! 👌

Burak BüyükyağmurTopic AuthorPosted on Version 3 of 3 • 7 months agoOptions

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Thanks for your lovely comment 😊

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